Overview

Dataset statistics

Number of variables15
Number of observations9250
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.1 MiB
Average record size in memory120.0 B

Variable types

Categorical1
Numeric14

Warnings

95% Speed(m/s) is highly correlated with 75% Speed(m/s) and 3 other fieldsHigh correlation
75% Speed(m/s) is highly correlated with 95% Speed(m/s) and 3 other fieldsHigh correlation
Mean Speed(m/s) is highly correlated with 95% Speed(m/s) and 2 other fieldsHigh correlation
Speed Std is highly correlated with 95% Speed(m/s) and 1 other fieldsHigh correlation
95% Acceleration(m^2/s) is highly correlated with Mean Acceleration(m^2/s) and 1 other fieldsHigh correlation
75% Acceleration(m^2/s) is highly correlated with Mean Acceleration(m^2/s) and 1 other fieldsHigh correlation
Mean Acceleration(m^2/s) is highly correlated with 95% Acceleration(m^2/s) and 2 other fieldsHigh correlation
Non 0 Mean Speed(m/s) is highly correlated with 95% Speed(m/s) and 2 other fieldsHigh correlation
Non 0 Mean Acceleration(m^2/s) is highly correlated with 95% Acceleration(m^2/s) and 2 other fieldsHigh correlation

Reproduction

Analysis started2021-05-09 07:27:30.230662
Analysis finished2021-05-09 07:28:07.839268
Duration37.61 seconds
Software versionpandas-profiling v2.11.0
Download configurationconfig.yaml

Variables

Labels
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size72.4 KiB
1
3831 
3
1832 
2
1515 
4
1340 
5
732 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters9250
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5
ValueCountFrequency (%)
13831
41.4%
31832
19.8%
21515
 
16.4%
41340
 
14.5%
5732
 
7.9%
2021-05-09T15:28:08.086593image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram of lengths of the category
2021-05-09T15:28:08.202451image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
ValueCountFrequency (%)
13831
41.4%
31832
19.8%
21515
 
16.4%
41340
 
14.5%
5732
 
7.9%

Most occurring characters

ValueCountFrequency (%)
13831
41.4%
31832
19.8%
21515
 
16.4%
41340
 
14.5%
5732
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number9250
100.0%

Most frequent character per category

ValueCountFrequency (%)
13831
41.4%
31832
19.8%
21515
 
16.4%
41340
 
14.5%
5732
 
7.9%

Most occurring scripts

ValueCountFrequency (%)
Common9250
100.0%

Most frequent character per script

ValueCountFrequency (%)
13831
41.4%
31832
19.8%
21515
 
16.4%
41340
 
14.5%
5732
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII9250
100.0%

Most frequent character per block

ValueCountFrequency (%)
13831
41.4%
31832
19.8%
21515
 
16.4%
41340
 
14.5%
5732
 
7.9%

Max Speed(m/s)
Real number (ℝ≥0)

Distinct3059
Distinct (%)33.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.63038486
Minimum0.28
Maximum99.88
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:08.340454image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0.28
5-th percentile2.6145
Q14.62
median8.83
Q319.7575
95-th percentile38.713
Maximum99.88
Range99.6
Interquartile range (IQR)15.1375

Descriptive statistics

Standard deviation13.37513611
Coefficient of variation (CV)0.9812735476
Kurtosis6.812160409
Mean13.63038486
Median Absolute Deviation (MAD)4.96
Skewness2.19827303
Sum126081.06
Variance178.894266
MonotocityNot monotonic
2021-05-09T15:28:08.503187image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5122
 
1.3%
4.9886
 
0.9%
4.9783
 
0.9%
4.9978
 
0.8%
4.9674
 
0.8%
4.9565
 
0.7%
4.9462
 
0.7%
4.9359
 
0.6%
4.958
 
0.6%
4.9255
 
0.6%
Other values (3049)8508
92.0%
ValueCountFrequency (%)
0.281
< 0.1%
0.481
< 0.1%
0.551
< 0.1%
0.611
< 0.1%
0.651
< 0.1%
ValueCountFrequency (%)
99.881
< 0.1%
97.641
< 0.1%
96.981
< 0.1%
95.631
< 0.1%
95.441
< 0.1%

95% Speed(m/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2319
Distinct (%)25.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.977572973
Minimum0.25
Maximum67.38
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:08.688103image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0.25
5-th percentile1.79
Q12.91
median5.11
Q313.1875
95-th percentile22.7555
Maximum67.38
Range67.13
Interquartile range (IQR)10.2775

Descriptive statistics

Standard deviation8.478246975
Coefficient of variation (CV)0.9443807364
Kurtosis9.15631155
Mean8.977572973
Median Absolute Deviation (MAD)3
Skewness2.265726859
Sum83042.55
Variance71.88067177
MonotocityNot monotonic
2021-05-09T15:28:08.888717image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.8333
 
0.4%
3.3428
 
0.3%
3.0727
 
0.3%
2.8827
 
0.3%
2.9827
 
0.3%
2.4226
 
0.3%
2.7825
 
0.3%
2.3525
 
0.3%
2.5224
 
0.3%
2.2424
 
0.3%
Other values (2309)8984
97.1%
ValueCountFrequency (%)
0.251
< 0.1%
0.391
< 0.1%
0.471
< 0.1%
0.541
< 0.1%
0.561
< 0.1%
ValueCountFrequency (%)
67.381
< 0.1%
65.721
< 0.1%
65.381
< 0.1%
64.841
< 0.1%
64.631
< 0.1%

75% Speed(m/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1935
Distinct (%)20.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.249003243
Minimum0
Maximum67
Zeros1
Zeros (%)< 0.1%
Memory size72.4 KiB
2021-05-09T15:28:09.104837image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.19
Q11.73
median3.59
Q38.9
95-th percentile18.61
Maximum67
Range67
Interquartile range (IQR)7.17

Descriptive statistics

Standard deviation6.643210418
Coefficient of variation (CV)1.063083208
Kurtosis9.419687429
Mean6.249003243
Median Absolute Deviation (MAD)2.11
Skewness2.458275108
Sum57803.28
Variance44.13224465
MonotocityNot monotonic
2021-05-09T15:28:09.305352image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.567
 
0.7%
1.7260
 
0.6%
1.4456
 
0.6%
1.5652
 
0.6%
1.652
 
0.6%
1.4852
 
0.6%
1.6252
 
0.6%
1.5451
 
0.6%
1.7450
 
0.5%
1.7850
 
0.5%
Other values (1925)8708
94.1%
ValueCountFrequency (%)
01
< 0.1%
0.11
< 0.1%
0.121
< 0.1%
0.151
< 0.1%
0.171
< 0.1%
ValueCountFrequency (%)
671
< 0.1%
55.381
< 0.1%
54.871
< 0.1%
54.381
< 0.1%
51.791
< 0.1%

Mean Speed(m/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1568
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.441460541
Minimum0.1
Maximum48.68
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:09.706355image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.89
Q11.39
median2.88
Q35.72
95-th percentile13.511
Maximum48.68
Range48.58
Interquartile range (IQR)4.33

Descriptive statistics

Standard deviation4.715008044
Coefficient of variation (CV)1.061589538
Kurtosis12.21328392
Mean4.441460541
Median Absolute Deviation (MAD)1.64
Skewness2.842656212
Sum41083.51
Variance22.23130085
MonotocityNot monotonic
2021-05-09T15:28:09.906858image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.4361
 
0.7%
1.4958
 
0.6%
1.2758
 
0.6%
1.2556
 
0.6%
1.3555
 
0.6%
1.1854
 
0.6%
1.4253
 
0.6%
1.4752
 
0.6%
1.3451
 
0.6%
1.3651
 
0.6%
Other values (1558)8701
94.1%
ValueCountFrequency (%)
0.11
< 0.1%
0.111
< 0.1%
0.171
< 0.1%
0.21
< 0.1%
0.211
< 0.1%
ValueCountFrequency (%)
48.681
< 0.1%
44.011
< 0.1%
42.011
< 0.1%
40.181
< 0.1%
39.971
< 0.1%

Speed Std
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1025
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.817126486
Minimum0.04
Maximum22.38
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:10.107458image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0.04
5-th percentile0.48
Q10.83
median1.41
Q34.4
95-th percentile7.66
Maximum22.38
Range22.34
Interquartile range (IQR)3.57

Descriptive statistics

Standard deviation2.716390077
Coefficient of variation (CV)0.9642414317
Kurtosis5.431724913
Mean2.817126486
Median Absolute Deviation (MAD)0.82
Skewness1.823737845
Sum26058.42
Variance7.378775048
MonotocityNot monotonic
2021-05-09T15:28:10.302608image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.9187
 
0.9%
0.7575
 
0.8%
0.7474
 
0.8%
0.8373
 
0.8%
0.7872
 
0.8%
0.7971
 
0.8%
0.8971
 
0.8%
0.7370
 
0.8%
0.8770
 
0.8%
0.7770
 
0.8%
Other values (1015)8517
92.1%
ValueCountFrequency (%)
0.041
 
< 0.1%
0.072
< 0.1%
0.083
< 0.1%
0.092
< 0.1%
0.13
< 0.1%
ValueCountFrequency (%)
22.381
< 0.1%
21.71
< 0.1%
20.531
< 0.1%
19.811
< 0.1%
19.151
< 0.1%

Max Acceleration(m^2/s)
Real number (ℝ≥0)

Distinct1467
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.835177297
Minimum0
Maximum81.74
Zeros18
Zeros (%)0.2%
Memory size72.4 KiB
2021-05-09T15:28:10.533889image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.22
Q11.48
median2.54
Q34.28
95-th percentile11.8455
Maximum81.74
Range81.74
Interquartile range (IQR)2.8

Descriptive statistics

Standard deviation4.833030018
Coefficient of variation (CV)1.260184248
Kurtosis37.11843603
Mean3.835177297
Median Absolute Deviation (MAD)1.28
Skewness4.653374335
Sum35475.39
Variance23.35817915
MonotocityNot monotonic
2021-05-09T15:28:10.734390image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0168
 
0.7%
0.0253
 
0.6%
2.9240
 
0.4%
2.5437
 
0.4%
2.8337
 
0.4%
2.5835
 
0.4%
1.7335
 
0.4%
2.8534
 
0.4%
2.6534
 
0.4%
2.534
 
0.4%
Other values (1457)8843
95.6%
ValueCountFrequency (%)
018
 
0.2%
0.0168
0.7%
0.0253
0.6%
0.0326
 
0.3%
0.0428
0.3%
ValueCountFrequency (%)
81.741
< 0.1%
79.521
< 0.1%
61.91
< 0.1%
60.831
< 0.1%
60.271
< 0.1%

95% Acceleration(m^2/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct452
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.092508108
Minimum0
Maximum29.14
Zeros21
Zeros (%)0.2%
Memory size72.4 KiB
2021-05-09T15:28:10.972649image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.12
Q10.6
median0.96
Q31.35
95-th percentile2.41
Maximum29.14
Range29.14
Interquartile range (IQR)0.75

Descriptive statistics

Standard deviation0.972513033
Coefficient of variation (CV)0.8901655061
Kurtosis164.5963756
Mean1.092508108
Median Absolute Deviation (MAD)0.37
Skewness8.365002549
Sum10105.7
Variance0.9457815993
MonotocityNot monotonic
2021-05-09T15:28:11.173145image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0498
 
1.1%
0.9897
 
1.0%
189
 
1.0%
1.0686
 
0.9%
0.9682
 
0.9%
0.0180
 
0.9%
0.9279
 
0.9%
0.7878
 
0.8%
0.8975
 
0.8%
0.9775
 
0.8%
Other values (442)8411
90.9%
ValueCountFrequency (%)
021
 
0.2%
0.0180
0.9%
0.0268
0.7%
0.0342
0.5%
0.0459
0.6%
ValueCountFrequency (%)
29.141
< 0.1%
24.841
< 0.1%
20.961
< 0.1%
19.521
< 0.1%
14.91
< 0.1%

75% Acceleration(m^2/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct190
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4313675676
Minimum0
Maximum11.97
Zeros71
Zeros (%)0.8%
Memory size72.4 KiB
2021-05-09T15:28:11.373661image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04
Q10.23
median0.4
Q30.57
95-th percentile0.92
Maximum11.97
Range11.97
Interquartile range (IQR)0.34

Descriptive statistics

Standard deviation0.3449227994
Coefficient of variation (CV)0.7996029959
Kurtosis210.5963962
Mean0.4313675676
Median Absolute Deviation (MAD)0.17
Skewness8.620445816
Sum3990.15
Variance0.1189717375
MonotocityNot monotonic
2021-05-09T15:28:11.636676image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.38186
 
2.0%
0.42179
 
1.9%
0.46177
 
1.9%
0.44169
 
1.8%
0.4165
 
1.8%
0.01161
 
1.7%
0.34157
 
1.7%
0.35156
 
1.7%
0.36156
 
1.7%
0.28151
 
1.6%
Other values (180)7593
82.1%
ValueCountFrequency (%)
071
0.8%
0.01161
1.7%
0.02127
1.4%
0.0371
0.8%
0.0456
 
0.6%
ValueCountFrequency (%)
11.971
< 0.1%
8.581
< 0.1%
7.851
< 0.1%
6.341
< 0.1%
4.721
< 0.1%

Mean Acceleration(m^2/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct182
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3443708108
Minimum0
Maximum9.66
Zeros80
Zeros (%)0.9%
Memory size72.4 KiB
2021-05-09T15:28:11.868442image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04
Q10.19
median0.31
Q30.4375
95-th percentile0.75
Maximum9.66
Range9.66
Interquartile range (IQR)0.2475

Descriptive statistics

Standard deviation0.2858025535
Coefficient of variation (CV)0.8299267665
Kurtosis189.3163166
Mean0.3443708108
Median Absolute Deviation (MAD)0.12
Skewness8.543771607
Sum3185.43
Variance0.08168309959
MonotocityNot monotonic
2021-05-09T15:28:12.078732image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.36238
 
2.6%
0.28233
 
2.5%
0.3230
 
2.5%
0.27222
 
2.4%
0.32222
 
2.4%
0.31221
 
2.4%
0.26210
 
2.3%
0.33207
 
2.2%
0.34203
 
2.2%
0.35200
 
2.2%
Other values (172)7064
76.4%
ValueCountFrequency (%)
080
0.9%
0.01161
1.7%
0.0294
1.0%
0.0366
0.7%
0.0484
0.9%
ValueCountFrequency (%)
9.661
< 0.1%
6.551
< 0.1%
5.721
< 0.1%
5.071
< 0.1%
5.011
< 0.1%

Acceleration Std
Real number (ℝ≥0)

Distinct272
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4532713514
Minimum0
Maximum13.85
Zeros77
Zeros (%)0.8%
Memory size72.4 KiB
2021-05-09T15:28:12.260891image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.05
Q10.24
median0.36
Q30.53
95-th percentile1.11
Maximum13.85
Range13.85
Interquartile range (IQR)0.29

Descriptive statistics

Standard deviation0.4796470403
Coefficient of variation (CV)1.058189623
Kurtosis166.3587026
Mean0.4532713514
Median Absolute Deviation (MAD)0.14
Skewness9.064500969
Sum4192.76
Variance0.2300612833
MonotocityNot monotonic
2021-05-09T15:28:12.553606image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.29224
 
2.4%
0.31213
 
2.3%
0.33212
 
2.3%
0.32210
 
2.3%
0.35208
 
2.2%
0.37199
 
2.2%
0.3199
 
2.2%
0.34193
 
2.1%
0.28190
 
2.1%
0.38186
 
2.0%
Other values (262)7216
78.0%
ValueCountFrequency (%)
077
0.8%
0.01142
1.5%
0.0274
0.8%
0.0358
0.6%
0.0465
0.7%
ValueCountFrequency (%)
13.851
< 0.1%
11.21
< 0.1%
10.071
< 0.1%
9.691
< 0.1%
9.351
< 0.1%

Non 0 Mean Speed(m/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct1565
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.503538378
Minimum0.11
Maximum48.68
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:12.795311image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0.11
5-th percentile0.93
Q11.41
median2.91
Q35.83
95-th percentile13.63
Maximum48.68
Range48.57
Interquartile range (IQR)4.42

Descriptive statistics

Standard deviation4.752298417
Coefficient of variation (CV)1.055236576
Kurtosis11.89158796
Mean4.503538378
Median Absolute Deviation (MAD)1.65
Skewness2.808585605
Sum41657.73
Variance22.58434024
MonotocityNot monotonic
2021-05-09T15:28:13.082264image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.3165
 
0.7%
1.463
 
0.7%
1.4362
 
0.7%
1.1958
 
0.6%
1.2557
 
0.6%
1.3457
 
0.6%
1.3256
 
0.6%
1.4855
 
0.6%
1.4455
 
0.6%
1.3355
 
0.6%
Other values (1555)8667
93.7%
ValueCountFrequency (%)
0.111
< 0.1%
0.121
< 0.1%
0.171
< 0.1%
0.231
< 0.1%
0.262
< 0.1%
ValueCountFrequency (%)
48.681
< 0.1%
44.011
< 0.1%
42.011
< 0.1%
40.451
< 0.1%
40.181
< 0.1%

Non 0 Mean Acceleration(m^2/s)
Real number (ℝ≥0)

HIGH CORRELATION

Distinct179
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3481351351
Minimum0
Maximum12.82
Zeros80
Zeros (%)0.9%
Memory size72.4 KiB
2021-05-09T15:28:13.309742image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.04
Q10.19
median0.31
Q30.44
95-th percentile0.76
Maximum12.82
Range12.82
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.2994945703
Coefficient of variation (CV)0.8602825169
Kurtosis380.4080606
Mean0.3481351351
Median Absolute Deviation (MAD)0.12
Skewness11.97018847
Sum3220.25
Variance0.08969699763
MonotocityNot monotonic
2021-05-09T15:28:13.591094image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.28229
 
2.5%
0.3227
 
2.5%
0.36225
 
2.4%
0.33225
 
2.4%
0.27222
 
2.4%
0.32220
 
2.4%
0.35216
 
2.3%
0.29212
 
2.3%
0.31208
 
2.2%
0.26193
 
2.1%
Other values (169)7073
76.5%
ValueCountFrequency (%)
080
0.9%
0.01162
1.8%
0.0297
1.0%
0.0366
0.7%
0.0483
0.9%
ValueCountFrequency (%)
12.821
< 0.1%
6.551
< 0.1%
5.721
< 0.1%
5.071
< 0.1%
5.011
< 0.1%

Total Time(s)
Real number (ℝ≥0)

Distinct3477
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1714.13827
Minimum10
Maximum66701
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:13.832665image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile150
Q1454.25
median928
Q31939.75
95-th percentile5470.55
Maximum66701
Range66691
Interquartile range (IQR)1485.5

Descriptive statistics

Standard deviation2817.611064
Coefficient of variation (CV)1.643747831
Kurtosis86.82160042
Mean1714.13827
Median Absolute Deviation (MAD)608
Skewness7.145271545
Sum15855779
Variance7938932.106
MonotocityNot monotonic
2021-05-09T15:28:14.074521image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11018
 
0.2%
31017
 
0.2%
10516
 
0.2%
50016
 
0.2%
52815
 
0.2%
20515
 
0.2%
60015
 
0.2%
22015
 
0.2%
44014
 
0.2%
28414
 
0.2%
Other values (3467)9095
98.3%
ValueCountFrequency (%)
102
< 0.1%
131
< 0.1%
142
< 0.1%
201
< 0.1%
241
< 0.1%
ValueCountFrequency (%)
667011
< 0.1%
499291
< 0.1%
475871
< 0.1%
441451
< 0.1%
386351
< 0.1%

Total Distance(m)
Real number (ℝ≥0)

Distinct9185
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10720.65672
Minimum100.67
Maximum1699909.78
Zeros0
Zeros (%)0.0%
Memory size72.4 KiB
2021-05-09T15:28:14.355530image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Quantile statistics

Minimum100.67
5-th percentile220.1005
Q1846.185
median2539.98
Q37520.585
95-th percentile31227.262
Maximum1699909.78
Range1699809.11
Interquartile range (IQR)6674.4

Descriptive statistics

Standard deviation48107.24781
Coefficient of variation (CV)4.4873415
Kurtosis362.9520225
Mean10720.65672
Median Absolute Deviation (MAD)2013.485
Skewness16.36280731
Sum99166074.65
Variance2314307291
MonotocityNot monotonic
2021-05-09T15:28:14.602904image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1155.612
 
< 0.1%
573.362
 
< 0.1%
887.52
 
< 0.1%
898.62
 
< 0.1%
1319.212
 
< 0.1%
2668.262
 
< 0.1%
1162.682
 
< 0.1%
755.782
 
< 0.1%
1410.482
 
< 0.1%
145.752
 
< 0.1%
Other values (9175)9230
99.8%
ValueCountFrequency (%)
100.671
< 0.1%
101.131
< 0.1%
101.331
< 0.1%
101.841
< 0.1%
102.251
< 0.1%
ValueCountFrequency (%)
1699909.781
< 0.1%
1154439.731
< 0.1%
1137144.571
< 0.1%
958678.311
< 0.1%
897497.331
< 0.1%

Interactions

2021-05-09T15:27:36.924629image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:37.178485image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:37.378978image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:37.526140image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:37.679834image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:37.849127image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.011947image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.181220image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.328351image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.466395image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.613532image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.782792image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:38.952058image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:39.114816image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:39.268443image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:39.426187image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:39.578526image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:39.741154image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:39.914741image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:40.089157image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:40.250435image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:40.405693image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:40.710301image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:40.876248image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:41.054641image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:41.214220image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:41.397770image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:41.552017image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:41.768146image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:42.068806image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:42.320740image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:42.559945image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:42.753923image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:42.938816image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:43.123672image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:43.308510image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:43.493416image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:43.662657image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:43.841042image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:44.010329image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:44.164023image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:44.311136image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:44.464791image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:44.596292image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:44.865884image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:45.052319image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:45.213507image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:45.398419image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:45.561116image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:45.768125image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:45.929144image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:46.107062image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:46.276312image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:46.413716image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:46.565814image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:46.725700image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:46.866323image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.013477image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.167229image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.330056image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.483781image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.630850image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.762334image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:47.900361image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:48.047495image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:48.201116image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:48.370353image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:48.633362image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:48.787011image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:48.949800image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:49.103479image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:49.272738image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:49.451112image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:49.597629image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:49.760948image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:49.913462image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:50.066685image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:50.240196image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:50.412082image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:50.547119image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:50.689897image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:50.863076image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.013906image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.148435image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.319991image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.467056image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.605071image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.736586image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:51.890209image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:52.168896image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:52.322601image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:52.491835image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:52.623324image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:52.792581image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:52.939748image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:53.093383image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:53.256119image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:53.440984image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:53.595599image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:53.739867image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:53.906373image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.037832image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.202982image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.356005image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.508569image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.652802image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.802781image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:54.949903image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:55.119145image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:55.266228image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:55.435502image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:55.682907image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:55.820973image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:55.983737image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:56.121770image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:56.284524image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:56.422607image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:56.585300image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:56.738951image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:56.886112image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.024184image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.186962image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.324994image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.509867image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.656978image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.810597image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:57.957714image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:58.112534image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:58.264699image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:58.427824image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:58.582074image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:58.732937image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:58.867753image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.133167image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.275291image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.407585image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.550130image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.692549image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.845368image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:27:59.988091image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:00.128206image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:00.283972image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:00.446736image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:00.600438image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:00.747610image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:00.901238image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.063973image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.201976image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.349087image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.502507image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.671825image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.819022image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:01.988407image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:02.135546image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:02.289160image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:02.451906image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:02.721454image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:02.868600image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:03.037889image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:03.175891image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:03.354272image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:03.507945image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:03.677242image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:03.855628image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.009288image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.156393image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.310024image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.479371image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.642134image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.827003image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:04.980625image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:05.159006image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:05.321218image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:05.475376image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:05.613444image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:05.798357image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:05.961092image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:06.126349image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:06.371303image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:06.535685image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:06.698467image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
2021-05-09T15:28:06.883333image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Correlations

2021-05-09T15:28:14.819441image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-05-09T15:28:15.304789image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-05-09T15:28:15.659839image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-05-09T15:28:16.215328image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2021-05-09T15:28:07.215389image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
A simple visualization of nullity by column.
2021-05-09T15:28:07.600860image/svg+xmlMatplotlib v3.4.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

LabelsMax Speed(m/s)95% Speed(m/s)75% Speed(m/s)Mean Speed(m/s)Speed StdMax Acceleration(m^2/s)95% Acceleration(m^2/s)75% Acceleration(m^2/s)Mean Acceleration(m^2/s)Acceleration StdNon 0 Mean Speed(m/s)Non 0 Mean Acceleration(m^2/s)Total Time(s)Total Distance(m)
0532.9832.5031.4117.8112.522.020.160.070.060.1921.280.0425599472373.57
1532.6432.2830.9920.6611.421.750.140.050.050.1522.250.0330608649395.24
2532.0630.7826.6420.918.332.980.120.050.050.1922.070.0317913376374.99
3532.4931.2328.0820.389.760.530.120.040.030.0621.350.0312925263477.50
4532.5632.0030.1622.679.160.320.110.050.040.0423.610.037289167948.25
5566.6450.8228.9726.5813.920.720.640.150.140.2226.580.14157235622.64
6530.0028.5925.6017.1610.331.270.070.030.030.0820.590.0233128573499.88
7529.3229.0926.2413.7811.660.860.130.070.070.1719.140.05161425445.85
8536.4727.2924.8019.117.342.600.120.040.070.3319.740.076313127255.13
9532.1830.6229.3618.0511.250.710.090.030.030.0721.260.028374154997.41

Last rows

LabelsMax Speed(m/s)95% Speed(m/s)75% Speed(m/s)Mean Speed(m/s)Speed StdMax Acceleration(m^2/s)95% Acceleration(m^2/s)75% Acceleration(m^2/s)Mean Acceleration(m^2/s)Acceleration StdNon 0 Mean Speed(m/s)Non 0 Mean Acceleration(m^2/s)Total Time(s)Total Distance(m)
924013.622.641.711.280.761.380.650.290.200.221.280.20380397.02
9241553.6120.1017.8012.327.5512.771.460.420.450.9412.390.45104213112.10
924214.903.372.061.461.022.831.050.460.350.371.460.3522443125.56
9243556.1322.5219.3015.846.7911.072.630.970.831.1815.840.8392213149.33
924414.883.421.601.211.061.441.010.340.270.321.220.27442411.31
9245314.1013.4610.897.084.232.361.070.470.370.357.080.373742646.72
924614.842.701.891.490.801.860.930.400.300.301.490.30494725.23
9247316.8415.2012.969.593.932.661.470.880.610.489.590.612122032.36
924814.182.351.341.010.851.730.860.280.220.311.010.22242530.16
9249522.6120.0118.2911.637.444.821.220.460.380.5611.660.38213618247.78